User-assisted Video Reflection Removal

TL;DR

This paper introduces a user-assisted video reflection removal method that leverages spatial, temporal, and sparse user hints to effectively separate reflection layers from videos, outperforming existing techniques.

Contribution

The novel approach combines motion cues and minimal user input to improve layer separation in reflection removal, addressing the ill-posed nature of the problem.

Findings

Significantly outperforms state-of-the-art methods

Removes reflections without visual distortions

Works on real and synthetic videos

Abstract

Reflections in videos are obstructions that often occur when videos are taken behind reflective surfaces like glass. These reflections reduce the quality of such videos, lead to information loss and degrade the accuracy of many computer vision algorithms. A video containing reflections is a combination of background and reflection layers. Thus, reflection removal is equivalent to decomposing the video into two layers. This, however, is a challenging and ill-posed problem as there is an infinite number of valid decompositions. To address this problem, we propose a user-assisted method for video reflection removal. We rely on both spatial and temporal information and utilize sparse user hints to help improve separation. The key idea of the proposed method is to use motion cues to separate the background layer from the reflection layer with minimal user assistance. We show that user-assistance significantly improves the layer separation results. We implement and evaluate the proposed method through quantitative and qualitative results on real and synthetic videos. Our experiments show that the proposed method successfully removes reflection from video sequences, does not introduce visual distortions, and significantly outperforms the state-of-the-art reflection removal methods in the literature.